Triple
T8178273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cajiqueño |
E190994
|
entity |
| Predicate | orthographicAccent |
P12752
|
FINISHED |
| Object | acute accent on é |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: acute accent on é | Statement: [Cajiqueño, orthographicAccent, acute accent on é]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: orthographicAccent Context triple: [Cajiqueño, orthographicAccent, acute accent on é]
-
A.
orthographicVariant
Indicates that two written forms are different spellings or orthographic representations of the same linguistic item.
-
B.
orthographicPattern
Indicates a relationship where entities share or follow a specific arrangement of written symbols, such as spelling or letter patterns.
-
C.
orthographicProperty
chosen
Indicates a relationship where a specific written or spelling-related characteristic is attributed to or associated with an entity.
-
D.
orthographicMedium
Indicates the writing system, script, or orthographic form through which something (such as a text, name, or expression) is represented.
-
E.
hasOrthographicConvention
Indicates that there is a specific writing or spelling convention that governs how something is represented in written form.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca82c4538081909404325aa5639483 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4abb66bc81908d758c7af2e23ac6 |
completed | March 31, 2026, 4:16 a.m. |
| PD | Predicate disambiguation | batch_69cb36a7952481908f34e3e82f375a84 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:40 p.m.